Finite time observer-based output feedback control of MEMS gyroscopes with input saturation

The finite time observer-based output feedback control of MEMS gyroscopes with input saturation is addressed in this article. For the unmeasured speed signal, neural network (NN) learning-based finite time observer is designed to observe the speed signal in finite time, where the adaptive NN is employed to approximate the nonlinear dynamics with system uncertainties. Considering the input saturation, an auxiliary system is introduced to design the anti-saturation compensator, such that the actual controller can escape saturation with less time and faster convergence can be achieved. Then the anti-saturation compensator further works together with output feedback controller to control the dynamics of MEMS gyroscopes. Simulation results are given to verify the faster speed observation and faster convergence of the proposed controller under input saturation.